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Found 2,700 Skills
Expert in Jira operations using Atlassian MCP - automatically detects workspace Jira configuration or prompts for project details. Use for searching, creating, updating issues, managing status transitions, and handling tasks.
Provides comprehensive guidance for searching and retrieving Maven components from Maven Central Repository (https://repo1.maven.org/maven2/). This skill enables searching by groupId, artifactId, version, and other coordinates, retrieving component metadata (POM files, JARs, sources, Javadoc), querying version history, and analyzing dependencies. Use when the user needs to find, verify, or retrieve Maven dependencies, check component versions, analyze dependency trees, or work with Maven coordinates.
Guide for creating AI subagents with isolated context for complex multi-step workflows. Use when users want to create a subagent, specialized agent, verifier, debugger, or orchestrator that requires isolated context and deep specialization. Works with any agent that supports subagent delegation. Triggers on "create subagent", "new agent", "specialized assistant", "create verifier".
AWS Identity and Access Management for users, roles, policies, and permissions. Use when creating IAM policies, configuring cross-account access, setting up service roles, troubleshooting permission errors, or managing access control.
Use when implementing motion design, timeline animations, visual animation editors, animating Three.js/R3F scenes, creating keyframe animations, or using Theatre.js, @theatre/core, @theatre/studio, @theatre/r3f, theatric, or building animation tooling for the web.
Break LLM name defaults with external entropy. Use when character names cluster around statistical medians (Chen, Patel, Maya, Marcus), when cast has collision risks, or when fantasy cultures need phonologically consistent naming.
An analytical in-process SQL database management system. Designed for fast analytical queries (OLAP). Highly interoperable with Python's data ecosystem (Pandas, NumPy, Arrow, Polars). Supports querying files (CSV, Parquet, JSON) directly without an ingestion step. Use for complex SQL queries on Pandas/Polars data, querying large Parquet/CSV files directly, joining data from different sources, analytical pipelines, local datasets too big for Excel, intermediate data storage and feature engineering for ML.
Astro-specific performance optimizations for 95+ Lighthouse scores. Covers critical CSS inlining, compression, font loading, and LCP optimization. Triggers on: astro performance, astro lighthouse, astro optimization, astro-critters.
SRE patterns for production service reliability: SLOs, error budgets, postmortems, and incident response. Use when defining reliability targets, writing postmortems, implementing SLO alerting, or establishing on-call practices. NOT for initial service development (use scaffolding skills instead).
Production-grade Helm 4 chart development, release management, and debugging. This skill should be used when users ask to create Helm charts, deploy with Helm, manage releases (install/upgrade/rollback), push charts to OCI registries, debug failed deployments, configure chart dependencies, create umbrella charts, set up GitOps with ArgoCD/Flux, or troubleshoot Helm issues. Auto-detects from Dockerfile/code, generates production-hardened charts with library patterns. Complements kubernetes skill.
Expertise in Go programming according to the Google Go Best Practices. Focuses on actionable advice for naming, error handling, performance, testing, and general idiomatic Go to ensure high-quality, maintainable, and efficient codebases.
Document and communicate plans clearly. Structures implementation plans with tasks, decisions, and success criteria.